AI Transformation in Insurance
For insurance companies finding and building customer relationships and managing risks are key to creating a growing, profitable business. Companies that are making extensive use of AI are reaping the benefits of increased customer satisfaction and loyalty while decreasing fraud which adds to their bottom line.
These companies are using AI for a number of scenarios including risk management, fraud detection, customer retention, and optimized marketing. WooHoo AI , the open source and automation leader in AI, is empowering leading insurance companies to deliver AI solutions that are changing the industry.
Finding and Stopping Fraud with AI
According to the FBI, the total cost of insurance fraud (non-health insurance) is estimated to be more than $40 billion per year, which costs average U.S. family between $400 and $700 per year in increased premiums.
Insurance claims processing is a tedious work which leads to errors. Some fraud types are well known and can be spotted using rules-based systems. However, new or more nuanced fraud is missed by rules-based systems until that fraud becomes well documented.
AI is ideally suited to fraud detection for insurance claims. Machine learning models can be used to automate claims assessment and routing based on existing fraud patterns. This process flags potentially fraudulent claims for further review, but also has the added benefit of automatically identifying good transactions and streamlining their approval and payment.
More advanced anomaly detection systems can be deployed to find new patterns and to flag those for review, which leads to prompt investigation of new fraud types. AI systems can also provide clear reason codes for investigators, so they can quickly see the key factors that led the AI to indicate fraud which streamlines their investigation. With AI based fraud detection, fraudulent claims can be evaluated and flagged before they are paid, which reduces costs for insurance providers and helps reduce costs for consumers.
AI Helps Retain Valuable Insurance Customers
It is widely known in the Insurance industry that retaining a customer is much more cost effective than acquiring a new one. More importantly, high value customers often have a portfolio of products including multiple policies making them even more painful to lose.
Simple churn analysis uses rules based on known behaviors to identify potential churn risks. Rules-based systems, however, are inflexible and miss many customers who leave and generate false positives that end up giving expensive incentives to customers who do not need them.
AI is a great solution for customer churn prediction as the problem involves complex data over time and interactions between different customer behaviors that can be difficult for people to identify. AI can look at a variety of data, including new data sources, and at relatively complex interactions between behaviors and compared to individual history to determine risk.
AI can also be used to recommend the best offer that will most likely retain a valuable customer. In addition, AI can identify the reasons why a customer is at risk and allow insurance company to act against those areas for the individual customer and more globally.
Streamlining the Claims Process with AI
For a consumer who has just been in an auto accident or experienced damage to their home, the processes of filing an insurance claim is often a make or break moment for the relationship with their insurance provider.
The assessment and payment of the claim should be fast and accurate to ensure customer satisfaction and prevent issues like fraud. Traditional claims management processes are manual with analysts and rules-based systems making choices in claims processing which can slow down the process and make it opaque to consumers and result in a poor customer experience.
AI is ideal for automating repetitive processes and finding anomalous behavior that may indicate fraud or other issues. AI can streamline processing by scoring claims for issues like fraud and allowing claims with low probability of an issue to be processed automatically while higher probability claims are routed to investigators for review.
AI models can also provide reason codes for claims denials, which streamlines the review process by allowing the analyst to quickly resolve those issues, so the claim can go through, or by showing the investigator the key issues to focus on. Reason codes are also helpful for customers because they can inform them of issues with their claim which can help them to fix the claim for reprocessing, approval and payment.
Personalized Product Bundling
Bundling the Right Product with AI
According to a study by J.D. Power & Associates, 46% of customers who own a bundle of insurance services say they “definitely will” renew with their provider vs. 28% of non-bundle policyholders.
With a large variety of products to choose from, the pressure to retain customers, and consumer expectations for personalized treatment, marketing and selling generic products is no longer an option. For insurance companies this means finding the right products to cross-sell into customers is critical for success.
AI is well known for helping to recommend products and drive personalization on retail sites and customers have come to expect personalized experiences. According to an Accenture study, more than 80% of insurance customers are looking for more personalized experiences. AI is equally well suited to recommend products and pricing in insurance.
With AI models, insurance companies can determine which products and policy options are the best fit for a given consumer. AI can also determine an individualized price based on consumer behavior and historical data. These recommendations can be used in web-based, call center and agent selling scenarios.